基于高阶统计量的亚奈奎斯特采样PSK信号自动调制识别
信息论
2015-01-05 v1 math.IT
摘要
N次幂非线性变换(NPT)方法所需的采样率通常远高于奈奎斯特率，这给模数转换器(ADC)带来了沉重负担。利用PSK信号在NPT下频谱的稀疏性，我们为PSK信号开发了基于亚奈奎斯特率采样的NPT方法。本文将NPT方法与压缩感知(CS)理论相结合，提出了PSK信号的N次幂非线性变换的频谱重建，该重建可进一步用于自动调制识别(AMR)以及对未知载波频率和符号率的粗略估计。
引用
@article{arxiv.1501.00158,
title = {Automatic Modulation Recognition of PSK Signals with Sub-Nyquist Sampling Based on High Order Statistics},
author = {Zhengli Xing and Jie Zhou and Jiangfeng Ye and Jun Yan and Jifeng Zou and Lin Zou and Qun Wan},
journal= {arXiv preprint arXiv:1501.00158},
year = {2015}
}
备注
7 pages, 8 figures, submitted to IEEE International Symposium on Signal Processing and Information Technology